How to Clean a CSV for Klaviyo Import: Prevent Rejected Profiles and Formatting Errors

Klaviyo Import Requirements

Klaviyo organizes contacts as profiles. Each profile requires at least one identifier: an email address, a phone number, or an external ID. Email is the primary identifier for most Klaviyo accounts and the one used for deduplication. When you import a CSV, Klaviyo checks each row for a valid email address. If the email is malformed, missing the @ symbol, contains spaces, or has an invalid domain structure, the entire row is rejected. The profile is not created, and any other data in that row (name, phone, custom properties) is lost.

For SMS marketing, Klaviyo requires phone numbers in E.164 format: plus sign, country code, subscriber number, no formatting characters. This is the same requirement used by Twilio (which powers Klaviyo's SMS infrastructure), Facebook Custom Audiences, and Google Ads Customer Match. Numbers that do not conform to E.164 are either rejected or stored incorrectly, which means your SMS flows and campaigns will skip those contacts entirely.

Beyond the core identifiers, Klaviyo supports custom properties for segmentation, personalization, and flow triggers. These properties have their own formatting requirements depending on the data type: dates must follow a consistent format, numbers must be numeric (no currency symbols or commas), and boolean fields must use true/false. Getting these wrong does not reject the profile, but it corrupts your ability to segment and personalize, which is the entire point of importing detailed customer data into Klaviyo.

Klaviyo Field Mapping Reference

Common Klaviyo Import Errors and How to Prevent Them

Rejected Profiles from Malformed Emails

Klaviyo validates email addresses during import and rejects profiles with invalid emails. Common causes include missing @ symbols, spaces within the address, double dots in the domain (user@example..com), and addresses with trailing commas or semicolons copied from email client address books. Unlike some platforms that silently accept bad emails, Klaviyo stops you at the import step. This is actually good because it prevents you from filling your account with undeliverable contacts, but it means you need to clean your emails before importing or you will lose those profiles entirely.

Use NoSheet's email validator to check every address before importing. The validator catches syntax errors, invalid domains, disposable providers, and common typos like gmial.com and yaho.com. Fix what can be fixed and remove what cannot, so your import completes with zero rejections. For a complete email cleaning workflow, see our email list cleaning guide.

SMS Flows Skipping Contacts with Bad Phone Numbers

Klaviyo's SMS features require phone numbers in E.164 format. If a profile's phone number is stored as (415) 555-1234 or 415-555-1234, Klaviyo cannot use it for SMS. The profile will exist in your account, but it will be excluded from every SMS flow and campaign. This is invisible unless you audit your SMS-eligible audience, which means you might have thousands of contacts with phone numbers that are technically present but functionally useless for SMS.

The fix is straightforward: convert all phone numbers to E.164 before import. The phone number formatter handles this in seconds, including country code detection for international numbers. If you are migrating from another SMS platform that stored numbers in a different format, this conversion is essential.

Missing or Incorrect Consent Status

Klaviyo takes consent seriously, especially for SMS. Importing a contact with a phone number but without explicit SMS consent status means Klaviyo will not send them SMS messages until they opt in through a Klaviyo form or flow. If you are migrating from another platform where these contacts had already opted in, you need to include the consent status in your CSV. The column should be named sms_consent and contain true or false. Without this, your entire SMS list starts from zero regardless of previous consent.

Email consent works similarly but is less strictly gated by default. Klaviyo allows you to import contacts as subscribed, but you are responsible for ensuring those contacts actually consented. Importing a purchased list as subscribed is a violation of Klaviyo's acceptable use policy and can result in account suspension.

Wrong Date Formats Breaking Segmentation

Date properties in Klaviyo should be in YYYY-MM-DD or full ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ). If your CSV contains dates in MM/DD/YYYY, DD/MM/YYYY, or any other format, Klaviyo may interpret them incorrectly or store them as text strings rather than date objects. When a date is stored as text, date-based segments ("purchased in the last 30 days," "birthday this month") will not include that contact because Klaviyo cannot perform date arithmetic on a text string. The contact looks like they have no purchase date or no birthday, even though the data exists.

This is especially dangerous with ambiguous dates. Is 03/04/2026 March 4 or April 3? Depending on the locale of the system that generated the CSV, either interpretation is possible. Standardizing all dates to YYYY-MM-DD before import eliminates this ambiguity entirely. Use NoSheet's date standardizer to convert any date format to ISO 8601 automatically.

Duplicate Profiles from Inconsistent Email Formatting

Klaviyo deduplicates on email address, and it does normalize email casing during import. So John@Example.com and john@example.com will not create duplicates. However, emails with typos or variations will. If one system recorded a contact as john@example.com and another recorded the same person as john@exmple.com (missing the 'a'), Klaviyo will create two separate profiles for the same person. This corrupts your segmentation, inflates your contact count (which affects billing), and can cause the same person to receive duplicate messages.

The 6-Step Pre-Import Cleaning Process

Step 1: Validate All Email Addresses

Run every email through validation to catch syntax errors, invalid domains, and common typos. Fix correctable issues (gmial.com to gmail.com, trailing spaces) and remove addresses that are fundamentally broken (no @ symbol, no domain). This step prevents rejected profiles during import and ensures Klaviyo can use every email for sending. The email validator handles this automatically, flagging each address as valid, correctable, or invalid.

Step 2: Format All Phone Numbers to E.164

Convert every phone number to E.164: plus sign, country code, subscriber number, no spaces or punctuation. This ensures Klaviyo can use the numbers for SMS flows and campaigns. Without E.164 formatting, the numbers are stored but non-functional for SMS. The phone formatter converts any input format to E.164 and flags numbers that cannot be converted (too few digits, unknown country code, invalid structure).

Step 3: Standardize All Date Fields

Convert every date column to YYYY-MM-DD format. This includes purchase dates, signup dates, birthdays, subscription renewal dates, and any other custom date property. Mixed date formats in a single column are especially dangerous because Klaviyo may interpret some correctly and others incorrectly, creating inconsistent data within the same property. The date standardizer detects the input format for each cell and converts it consistently, even when the column contains mixed formats.

Step 4: Deduplicate on Email Address

Remove duplicate rows based on email address. Although Klaviyo handles deduplication during import, importing duplicates creates unnecessary processing overhead and can cause confusing import reports. When duplicates exist, decide which row to keep: the one with the most populated fields, the most recent activity date, or the highest lifetime value. Deduplication after normalization is important because lowercasing emails and fixing typos may reveal duplicates that were previously hidden.

Step 5: Set Consent Fields

If your contacts have existing consent status from another platform, include it in your CSV. Add an sms_consent column with true or false for each row. For email consent, use a column indicating whether the contact is subscribed, unsubscribed, or has never been set. Do not mark contacts as subscribed unless you have legitimate proof of consent. Klaviyo monitors list quality and will flag or suspend accounts that import large numbers of non-consented contacts.

Step 6: Remove Invalid and Placeholder Data

Remove rows where the email or phone is clearly a test entry (test@test.com, 555-555-5555), a placeholder (noemail@noemail.com, 0000000000), or an internal address (admin@yourcompany.com). These entries inflate your contact count, affect your billing (Klaviyo charges by active profiles), and skew your campaign metrics. Also remove any columns that do not map to Klaviyo properties or custom properties you have defined. Extra columns create mapping confusion during import and may accidentally create unwanted custom properties.

Klaviyo Import Tips and Best Practices

Column naming matters. Klaviyo attempts to auto-map CSV columns to profile properties based on column headers. Using email, phone_number, first_name, and last_name as your column headers ensures automatic mapping. Non-standard headers like "Email Address," "Mobile Phone," or "Given Name" may require manual mapping during import.

Custom properties are case-sensitive. A custom property called lifetime_value is different from Lifetime_Value in Klaviyo. If you import the same data with inconsistent property names across multiple imports, you will create duplicate properties with different capitalizations, fragmenting your data. Decide on a naming convention (lowercase_with_underscores is recommended) and use it consistently across all imports.

Test with a small batch first. Before importing your full 50,000-contact file, import a sample of 100 rows. Verify that all fields map correctly, dates are interpreted properly, phone numbers are recognized for SMS, and no profiles are rejected. Fix any issues in the sample, apply the same fixes to the full file, and then import. This two-minute test saves hours of cleanup after a botched full import.

If you are migrating from Mailchimp, the field mapping is slightly different. Mailchimp uses Email Address as the column header while Klaviyo expects email. Mailchimp stores phone numbers in national format while Klaviyo requires E.164. Our guide on cleaning CSVs for Mailchimp covers the Mailchimp side if you need to export from there first.

How NoSheet Prepares Your Data for Klaviyo in Minutes

NoSheet handles every step of the Klaviyo pre-import process. Upload your CSV and run email validation, phone E.164 formatting, date standardization, and deduplication in sequence. Each operation runs in seconds on the Rust backend, and the transformations are applied to your full dataset without row limits or file size caps. The output is a clean, Klaviyo-ready CSV with validated emails, E.164 phones, ISO dates, and no duplicates.

The manual approach involves writing validation formulas in a spreadsheet, manually checking date formats, and running multiple sort-and-filter passes to find duplicates. On a 20,000-row file, that process easily takes an hour or more. On NoSheet, the same file is cleaned in under two minutes. For teams that import data into Klaviyo regularly (weekly campaign lists, monthly CRM syncs, quarterly migration batches), the time savings compound into dozens of hours per year. For more on general pre-campaign data preparation, see our data cleaning before a campaign guide.

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